Research On Location Privacy Protection Method Based On K-anonymity Algorithm

Location based service(LBS)requires that the user provide the location information to the LBS server when having queries to the LBS server,then the LBS server processes the query based on the location-based information and returns the results of query to the user.People expose their position to the LBS server to obtain the high quality service,but also may leak the location privacy.In the traditional privacy protection algorithm,the location ?-anonymity algorithm is the most used anonymous protection method.However,if the attacker obtains the historical query probability,the query time and the content of query,they can infer the personal sensitive information of users according to the side information,so the users' location privacy is exposed.The proposed entropy-anonymity algorithm guarantees the consistency of the query probability of k users in the cloaking region to solve the above problem.However,encountering the scenarios of clustering around each other in cloaking region in the entropy-anonymity algorithm,which will cause the real location of user to be exposed.In order to solve this problem,this paper introduces the UCD(user cloaking distance)and RCD(region cloaking distance),and proposes the Optimal Distance(OD)algorithm,it calculates the average distance and the distance variance between users in the cloaking area by the innovative calculation method.The Optimal Distance algorithm not only require to increase the average distance of k users but also require to decrease the variance distance of k users' location,it is key that we limit the size of cloaking region.It not only solves the problem that users are located close together in the cloaking region,but also ensures the quality of service obtained by the user.For inferring attacks based on time and content relevance,we introduce the parameter,Ri.j,to measure the relevance of time and content,then we present a novel method to quantify the degree of the relevance.With the quantification method we generate a S-1 dummy CRs which is isomorphic.Since the attackers only obtain a number of indistinguishably real and fake information,the track of a real user will be blurred by sending a certain copies of the same queries simultaneously from many CR candidates.Combine the two algorithms together,a new method called Content-Aware Location-Obfuscated is proposed to synthetically solve problems of users' distance and time and content relevance.The integrated method can solve the privacy problems caused by multiple scenarios together,and give users a more comprehensive location privacy protection,and the method has better performance in the system resource cost.Extensive evaluations are performed to verify our privacy model.Results demonstrate that the proposed algorithms guarantees a high level of privacy compared with DLS algorithm and enhanced-DLS algorithm,and do well in hidden degree,service quality and system resource overhead.